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August 16, 2025Applied SciencesOpen Access

A Multimodal Bone Stick Matching Approach Based on Large-Scale Pre-Trained Models and Dynamic Cross-Modal Feature Fusion

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A multimodal matching technique improves accuracy in fragmented bone stick artifacts, indicating advanced digital preservation methods.

The matching accuracy achieved 94.73% at Rank-15, highlighting significant improvements over conventional methods.
Integration of image, inscription, and archaeological information enhances efficiency and preserves artifacts effectively.
Dynamic cross-modal feature fusion enables better interaction and weighting of visual and textual features for matching.
This method overcomes limitations of traditional image-based approaches, offering robust support for cultural heritage restoration.

Fan et al. (2025) studied this question.

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